Diagnostics and prognostics utilising dynamic Bayesian networks applied to a wind turbine gearbox
, 2012 The UK has the largest installed capacity of offshore wind and this is set to increase significantly in future years. The difficulty in conducting maintenance offshore leads to increased operation and maintenance costs compared to onshore but with better
Wilson, Graeme +4 more
core
Advanced Science, EarlyView.Single‐cell and spatial profiling of 110 human thoracic aortic samples reveals a stromal–immune circuit driving aortic dissection. An elastin‐rich fibroblast subset is depleted with age and markedly reduced in disease, weakening aortic wall integrity.
Jing Tao +25 more
wiley +1 more source
Dynamic Bayesian networks for prediction of health status and treatment effect in patients with chronic lymphocytic leukemia. [PDF]
Sci Rep, 2022 Ladyzynski P, Molik M, Foltynski P.
europepmc +1 more source
Compiling Dynamic Fault Trees into Dynamic Bayesian Networks: the RADYBAN Tool
, 2007 In this paper, we present Radyban (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze systems modeled by means of Dynamic Fault Trees (DFT), by relying on automatic conversion into Dynamic Bayesian Networks
MONTANI, Stefania +3 more
core
Bayesian representations using chain event graphs [PDF]
, 2006 Bayesian networks (BNs) are useful for coding conditional independence statements between a given set of measurement variables. On the other hand, event trees (ETs) are convenient for representing asymmetric structure and how situations unfold.
Smith, J. Q., Anderson, Paul E.
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Advanced Science, EarlyView.STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu +5 more
wiley +1 more source
Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes. [PDF]
Comput Methods Programs Biomed, 2022 Longato E +13 more
europepmc +1 more source
Optimising ITS behaviour with Bayesian networks and decision theory
, 2001 We propose and demonstrate a methodology for building tractable normative intelligent tutoring systems (ITSs). A normative ITS uses a Bayesian network for long-term student modelling and decision theory to select the next tutorial action.
Mitrovic, Antonija, Mayo, Michael
core
Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)
, 2012 The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions.
Mathew, Joseph +7 more
core +1 more source
A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces
Advanced Science, EarlyView.A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren +5 more
wiley +1 more source